Overview

Dataset statistics

Number of variables10
Number of observations17898
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory80.0 B

Variable types

NUM9
BOOL1

Reproduction

Analysis started2020-08-10 12:55:59.788479
Analysis finished2020-08-10 12:56:32.179830
Duration32.39 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

skew_pf is highly correlated with ex_kurt_pfHigh correlation
ex_kurt_pf is highly correlated with skew_pfHigh correlation
skew_dm is highly correlated with kurt_dmHigh correlation
kurt_dm is highly correlated with skew_dmHigh correlation
df_index has unique values Unique
skew_pf has unique values Unique

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct count17898
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8949.5
Minimum1
Maximum17898
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:32.384809image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile895.85
Q14475.25
median8949.5
Q313423.75
95-th percentile17003.15
Maximum17898
Range17897
Interquartile range (IQR)8948.5

Descriptive statistics

Standard deviation5166.851895
Coefficient of variation (CV)0.577334141
Kurtosis-1.2
Mean8949.5
Median Absolute Deviation (MAD)4474.5
Skewness0
Sum160178151
Variance26696358.5
2020-08-10T18:26:32.696811image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20471< 0.1%
 
47591< 0.1%
 
88491< 0.1%
 
149941< 0.1%
 
129471< 0.1%
 
27081< 0.1%
 
6611< 0.1%
 
68061< 0.1%
 
170531< 0.1%
 
47751< 0.1%
 
109121< 0.1%
 
88651< 0.1%
 
150101< 0.1%
 
129631< 0.1%
 
27241< 0.1%
 
6771< 0.1%
 
108961< 0.1%
 
170371< 0.1%
 
47431< 0.1%
 
67901< 0.1%
 
6451< 0.1%
 
26921< 0.1%
 
129311< 0.1%
 
149781< 0.1%
 
88331< 0.1%
 
Other values (17873)1787399.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
178981< 0.1%
 
178971< 0.1%
 
178961< 0.1%
 
178951< 0.1%
 
178941< 0.1%
 
178931< 0.1%
 
178921< 0.1%
 
178911< 0.1%
 
178901< 0.1%
 
178891< 0.1%
 

mean_int_pf
Real number (ℝ≥0)

Distinct count8626
Unique (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.07996834492681
Minimum5.8125
Maximum192.6171875
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:33.008811image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum5.8125
5-th percentile57.49179688
Q1100.9296875
median115.078125
Q3127.0859375
95-th percentile143.0726562
Maximum192.6171875
Range186.8046875
Interquartile range (IQR)26.15625

Descriptive statistics

Standard deviation25.65293536
Coefficient of variation (CV)0.2309411476
Kurtosis2.972373829
Mean111.0799683
Median Absolute Deviation (MAD)12.921875
Skewness-1.375187645
Sum1988109.273
Variance658.0730926
2020-08-10T18:26:33.288807image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
106.7109375120.1%
 
112.914062590.1%
 
106.648437590.1%
 
124.54687590.1%
 
116.531258< 0.1%
 
119.30468758< 0.1%
 
122.2031258< 0.1%
 
120.156258< 0.1%
 
119.96093758< 0.1%
 
119.2968758< 0.1%
 
118.1718758< 0.1%
 
124.42968758< 0.1%
 
117.28906258< 0.1%
 
115.61718758< 0.1%
 
112.97656258< 0.1%
 
129.21093758< 0.1%
 
134.593758< 0.1%
 
105.24218758< 0.1%
 
116.11718758< 0.1%
 
124.13281258< 0.1%
 
123.031258< 0.1%
 
118.656258< 0.1%
 
115.2343758< 0.1%
 
127.46093758< 0.1%
 
117.8758< 0.1%
 
Other values (8601)1769198.8%
 
ValueCountFrequency (%) 
5.81251< 0.1%
 
6.17968751< 0.1%
 
6.18752< 0.1%
 
6.2656251< 0.1%
 
6.41406251< 0.1%
 
6.51< 0.1%
 
6.93751< 0.1%
 
6.9843751< 0.1%
 
7.03906251< 0.1%
 
7.06251< 0.1%
 
ValueCountFrequency (%) 
192.61718751< 0.1%
 
190.4218751< 0.1%
 
189.7343751< 0.1%
 
186.02343751< 0.1%
 
185.25781251< 0.1%
 
184.8281251< 0.1%
 
184.46093751< 0.1%
 
184.2968751< 0.1%
 
183.4531251< 0.1%
 
183.41406251< 0.1%
 

std_pf
Real number (ℝ≥0)

Distinct count17862
Unique (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.54953156153425
Minimum24.77204176
Maximum98.77891067
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:33.564806image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum24.77204176
5-th percentile34.71431588
Q142.37601758
median46.94747911
Q351.02320199
95-th percentile56.47375633
Maximum98.77891067
Range74.00686891
Interquartile range (IQR)8.647184407

Descriptive statistics

Standard deviation6.84318941
Coefficient of variation (CV)0.1470087707
Kurtosis1.689571384
Mean46.54953156
Median Absolute Deviation (MAD)4.28935198
Skewness0.1266410772
Sum833143.5159
Variance46.8292413
2020-08-10T18:26:33.813540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
42.312626942< 0.1%
 
51.042749182< 0.1%
 
38.904291342< 0.1%
 
47.466371222< 0.1%
 
45.035305162< 0.1%
 
44.397309532< 0.1%
 
43.404708852< 0.1%
 
46.843822972< 0.1%
 
44.448725622< 0.1%
 
40.75094662< 0.1%
 
48.912190132< 0.1%
 
43.360608092< 0.1%
 
51.943887222< 0.1%
 
44.552275742< 0.1%
 
50.185940882< 0.1%
 
46.208680212< 0.1%
 
44.774772732< 0.1%
 
43.545582712< 0.1%
 
49.196907362< 0.1%
 
51.829158962< 0.1%
 
40.466804372< 0.1%
 
46.40581862< 0.1%
 
46.521962222< 0.1%
 
50.21849722< 0.1%
 
46.402638222< 0.1%
 
Other values (17837)1784899.7%
 
ValueCountFrequency (%) 
24.772041761< 0.1%
 
24.791611961< 0.1%
 
24.898210751< 0.1%
 
25.220055681< 0.1%
 
25.695249551< 0.1%
 
25.771711071< 0.1%
 
26.122681151< 0.1%
 
26.179797081< 0.1%
 
26.337869121< 0.1%
 
26.429324931< 0.1%
 
ValueCountFrequency (%) 
98.778910671< 0.1%
 
91.80862791< 0.1%
 
91.206474731< 0.1%
 
90.250557261< 0.1%
 
90.157445561< 0.1%
 
86.951396481< 0.1%
 
86.239830411< 0.1%
 
85.970901181< 0.1%
 
85.797340251< 0.1%
 
85.320849741< 0.1%
 

ex_kurt_pf
Real number (ℝ)

HIGH CORRELATION

Distinct count17897
Unique (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.47785725810191076
Minimum-1.876011181
Maximum8.069522046
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:34.091537image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-1.876011181
5-th percentile-0.2316708194
Q10.02709812
median0.223240024
Q30.4733251825
95-th percentile2.706560919
Maximum8.069522046
Range9.945533227
Interquartile range (IQR)0.4462270625

Descriptive statistics

Standard deviation1.064039716
Coefficient of variation (CV)2.226689452
Kurtosis14.63974212
Mean0.4778572581
Median Absolute Deviation (MAD)0.2166979535
Skewness3.638409664
Sum8552.689206
Variance1.132180518
2020-08-10T18:26:34.322545image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.0019342822< 0.1%
 
0.1994906561< 0.1%
 
0.1874853781< 0.1%
 
0.3206348941< 0.1%
 
-0.0192105241< 0.1%
 
-0.1751379951< 0.1%
 
0.5758915451< 0.1%
 
0.1147049411< 0.1%
 
0.6539693791< 0.1%
 
-0.026661421< 0.1%
 
0.133161831< 0.1%
 
-0.1131204821< 0.1%
 
-0.0100688221< 0.1%
 
0.1171761551< 0.1%
 
5.6436413781< 0.1%
 
0.5693658671< 0.1%
 
0.2573408271< 0.1%
 
0.1484800951< 0.1%
 
0.2634758831< 0.1%
 
0.3281520921< 0.1%
 
0.389442031< 0.1%
 
-0.1487220711< 0.1%
 
0.0707299971< 0.1%
 
-0.0838114111< 0.1%
 
-0.0745066071< 0.1%
 
Other values (17872)1787299.9%
 
ValueCountFrequency (%) 
-1.8760111811< 0.1%
 
-1.7380207621< 0.1%
 
-1.7307817241< 0.1%
 
-1.7077890781< 0.1%
 
-1.6790393391< 0.1%
 
-1.6690322781< 0.1%
 
-1.641515441< 0.1%
 
-1.6339224951< 0.1%
 
-1.6242694711< 0.1%
 
-1.6048290881< 0.1%
 
ValueCountFrequency (%) 
8.0695220461< 0.1%
 
7.8796276781< 0.1%
 
7.8757420911< 0.1%
 
7.8563703861< 0.1%
 
7.6275802481< 0.1%
 
7.608369541< 0.1%
 
7.5950967841< 0.1%
 
7.5725765171< 0.1%
 
7.5509218941< 0.1%
 
7.5250275441< 0.1%
 

skew_pf
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct count17898
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7702789980713487
Minimum-1.7918859809999999
Maximum68.10162173
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:34.575536image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-1.791885981
5-th percentile-0.5563713136
Q1-0.1885716535
median0.198710401
Q30.9277830915
95-th percentile10.13850687
Maximum68.10162173
Range69.89350771
Interquartile range (IQR)1.116354745

Descriptive statistics

Standard deviation6.167913248
Coefficient of variation (CV)3.484147558
Kurtosis30.16647877
Mean1.770278998
Median Absolute Deviation (MAD)0.473095337
Skewness5.181293444
Sum31684.45351
Variance38.04315383
2020-08-10T18:26:34.848542image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.3720919631< 0.1%
 
0.4267538521< 0.1%
 
0.2422270361< 0.1%
 
-0.1415606721< 0.1%
 
1.7950396481< 0.1%
 
-0.4457931821< 0.1%
 
-0.5424984681< 0.1%
 
-0.0313135021< 0.1%
 
0.6264101971< 0.1%
 
0.7030464731< 0.1%
 
0.1923207721< 0.1%
 
-0.6114798411< 0.1%
 
-0.0927114251< 0.1%
 
-0.0977368451< 0.1%
 
-0.5042655251< 0.1%
 
1.9668702651< 0.1%
 
0.274225621< 0.1%
 
0.8736905321< 0.1%
 
-0.3600358831< 0.1%
 
1.4420201381< 0.1%
 
0.0199447331< 0.1%
 
0.5488976361< 0.1%
 
-0.3819560951< 0.1%
 
0.8459431691< 0.1%
 
1.9821359661< 0.1%
 
Other values (17873)1787399.9%
 
ValueCountFrequency (%) 
-1.7918859811< 0.1%
 
-1.7818883011< 0.1%
 
-1.7647174461< 0.1%
 
-1.7553316671< 0.1%
 
-1.6767241491< 0.1%
 
-1.6685403631< 0.1%
 
-1.6600491111< 0.1%
 
-1.602976691< 0.1%
 
-1.5981445861< 0.1%
 
-1.5936484571< 0.1%
 
ValueCountFrequency (%) 
68.101621731< 0.1%
 
65.385973851< 0.1%
 
63.466388351< 0.1%
 
63.149537411< 0.1%
 
62.868530871< 0.1%
 
58.29450111< 0.1%
 
57.504557741< 0.1%
 
57.175231651< 0.1%
 
57.070493161< 0.1%
 
56.900852221< 0.1%
 

mean_dm
Real number (ℝ≥0)

Distinct count9000
Unique (%)50.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.614399658311545
Minimum0.213210702
Maximum223.39214049999998
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:35.122539image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0.213210702
5-th percentile1.005852843
Q11.923076923
median2.801839465
Q35.464255853
95-th percentile82.96697325
Maximum223.3921405
Range223.1789298
Interquartile range (IQR)3.54117893

Descriptive statistics

Standard deviation29.47289715
Coefficient of variation (CV)2.336448658
Kurtosis14.06472096
Mean12.61439966
Median Absolute Deviation (MAD)1.178093646
Skewness3.683302122
Sum225772.5251
Variance868.6516664
2020-08-10T18:26:35.368541image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.294314381120.1%
 
2.050167224120.1%
 
1.423913043120.1%
 
2.33277592120.1%
 
2.418896321110.1%
 
2.193979933110.1%
 
2.086120401100.1%
 
2.211538462100.1%
 
1.918896321100.1%
 
2.060200669100.1%
 
2.029264214100.1%
 
1.72993311100.1%
 
1.777591973100.1%
 
2.0409699100.1%
 
2.290133779100.1%
 
1.940635452100.1%
 
2.116220736100.1%
 
2.930602007100.1%
 
2.010033445100.1%
 
2.06521739190.1%
 
1.99749163990.1%
 
2.02508361290.1%
 
2.25501672290.1%
 
2.11956521790.1%
 
2.07190635590.1%
 
Other values (8975)1764498.6%
 
ValueCountFrequency (%) 
0.2132107024< 0.1%
 
0.249163881< 0.1%
 
0.2734113711< 0.1%
 
0.2826086961< 0.1%
 
0.2892976591< 0.1%
 
0.29096991< 0.1%
 
0.3001672242< 0.1%
 
0.312709031< 0.1%
 
0.3160535121< 0.1%
 
0.3177257532< 0.1%
 
ValueCountFrequency (%) 
223.39214051< 0.1%
 
222.42140471< 0.1%
 
217.37123751< 0.1%
 
211.94899671< 0.1%
 
209.30016721< 0.1%
 
208.62959871< 0.1%
 
207.30267561< 0.1%
 
206.52926421< 0.1%
 
203.81772581< 0.1%
 
202.33193981< 0.1%
 

std_dm
Real number (ℝ≥0)

Distinct count17894
Unique (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.326514703918594
Minimum7.370432165
Maximum110.64221059999998
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:35.626540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum7.370432165
5-th percentile11.08234472
Q114.4373316
median18.46131559
Q328.42810432
95-th percentile74.62164202
Maximum110.6422106
Range103.2717784
Interquartile range (IQR)13.99077272

Descriptive statistics

Standard deviation19.47057233
Coefficient of variation (CV)0.7395803261
Kurtosis2.825997458
Mean26.3265147
Median Absolute Deviation (MAD)5.16221791
Skewness1.89425413
Sum471191.9602
Variance379.1031869
2020-08-10T18:26:35.863540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
7.3704321654< 0.1%
 
11.575121952< 0.1%
 
33.400236591< 0.1%
 
23.49475911< 0.1%
 
18.127697331< 0.1%
 
15.860515861< 0.1%
 
31.517617381< 0.1%
 
20.221558271< 0.1%
 
28.193808391< 0.1%
 
27.854739881< 0.1%
 
32.893814521< 0.1%
 
30.166055571< 0.1%
 
19.899108281< 0.1%
 
12.845197091< 0.1%
 
16.190837941< 0.1%
 
16.883190831< 0.1%
 
16.510209911< 0.1%
 
24.119503411< 0.1%
 
40.466479721< 0.1%
 
14.583268971< 0.1%
 
22.593141741< 0.1%
 
12.326753931< 0.1%
 
24.3108521< 0.1%
 
34.798020481< 0.1%
 
16.101693391< 0.1%
 
Other values (17869)1786999.8%
 
ValueCountFrequency (%) 
7.3704321654< 0.1%
 
7.44881661< 0.1%
 
7.4734619211< 0.1%
 
7.5649495381< 0.1%
 
7.5656616831< 0.1%
 
7.5656810881< 0.1%
 
7.6569199731< 0.1%
 
7.6586228071< 0.1%
 
7.6639102481< 0.1%
 
7.6646226391< 0.1%
 
ValueCountFrequency (%) 
110.64221061< 0.1%
 
109.71264911< 0.1%
 
109.65534511< 0.1%
 
108.93142681< 0.1%
 
108.71082651< 0.1%
 
108.07801911< 0.1%
 
107.94748951< 0.1%
 
107.45204591< 0.1%
 
107.43182321< 0.1%
 
106.79917431< 0.1%
 

kurt_dm
Real number (ℝ)

HIGH CORRELATION

Distinct count17895
Unique (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.303556116638282
Minimum-3.1392696110000005
Maximum34.53984419
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:36.139617image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-3.139269611
5-th percentile0.5309076095
Q15.781505744
median8.433514689
Q310.70295928
95-th percentile15.77067966
Maximum34.53984419
Range37.6791138
Interquartile range (IQR)4.921453539

Descriptive statistics

Standard deviation4.506091859
Coefficient of variation (CV)0.5426701278
Kurtosis1.526209366
Mean8.303556117
Median Absolute Deviation (MAD)2.424037602
Skewness0.4415008652
Sum148617.0474
Variance20.30486384
2020-08-10T18:26:36.401618image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
34.539844194< 0.1%
 
6.7971786661< 0.1%
 
2.201684581< 0.1%
 
1.7814915541< 0.1%
 
8.5845438751< 0.1%
 
5.2007294031< 0.1%
 
5.2236919681< 0.1%
 
7.7342900541< 0.1%
 
14.939612461< 0.1%
 
11.816920011< 0.1%
 
14.187990371< 0.1%
 
6.8020903021< 0.1%
 
7.9935628781< 0.1%
 
10.209459421< 0.1%
 
0.6479897491< 0.1%
 
13.223977641< 0.1%
 
0.1514869621< 0.1%
 
8.6281896061< 0.1%
 
5.0878117231< 0.1%
 
7.6635703711< 0.1%
 
10.034994921< 0.1%
 
7.6943368911< 0.1%
 
9.6485312331< 0.1%
 
17.428645861< 0.1%
 
6.3084923751< 0.1%
 
Other values (17870)1787099.8%
 
ValueCountFrequency (%) 
-3.1392696111< 0.1%
 
-2.8123533061< 0.1%
 
-2.7218571861< 0.1%
 
-2.6368573811< 0.1%
 
-2.5978718611< 0.1%
 
-2.5567951871< 0.1%
 
-2.5457335411< 0.1%
 
-2.5420253661< 0.1%
 
-2.5264296341< 0.1%
 
-2.4490085011< 0.1%
 
ValueCountFrequency (%) 
34.539844194< 0.1%
 
33.48975471< 0.1%
 
33.273410881< 0.1%
 
32.198584111< 0.1%
 
32.174189041< 0.1%
 
32.111415931< 0.1%
 
31.471559291< 0.1%
 
31.312267341< 0.1%
 
30.992919311< 0.1%
 
30.883882191< 0.1%
 

skew_dm
Real number (ℝ)

HIGH CORRELATION

Distinct count17895
Unique (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.85770870366203
Minimum-1.976975603
Maximum1191.0008369999998
Zeros0
Zeros (%)0.0%
Memory size140.0 KiB
2020-08-10T18:26:36.690548image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum-1.976975603
5-th percentile-0.4997202556
Q134.96050444
median83.06455613
Q3139.3093305
95-th percentile296.3790549
Maximum1191.000837
Range1192.977813
Interquartile range (IQR)104.3488261

Descriptive statistics

Standard deviation106.5145395
Coefficient of variation (CV)1.015800754
Kurtosis13.49411299
Mean104.8577087
Median Absolute Deviation (MAD)51.51510672
Skewness2.734513559
Sum1876743.27
Variance11345.34713
2020-08-10T18:26:37.240546image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1191.0008374< 0.1%
 
200.79893591< 0.1%
 
308.11887141< 0.1%
 
201.86208481< 0.1%
 
106.52269151< 0.1%
 
243.45105441< 0.1%
 
376.8086021< 0.1%
 
136.62486991< 0.1%
 
666.48796411< 0.1%
 
247.28638611< 0.1%
 
-0.4957185241< 0.1%
 
104.46313571< 0.1%
 
42.416948941< 0.1%
 
125.37468331< 0.1%
 
45.039015391< 0.1%
 
78.795654231< 0.1%
 
129.6092371< 0.1%
 
8.6470489481< 0.1%
 
63.873764771< 0.1%
 
77.152930221< 0.1%
 
621.42727511< 0.1%
 
19.415112281< 0.1%
 
80.799941071< 0.1%
 
71.827753221< 0.1%
 
208.36694491< 0.1%
 
Other values (17870)1787099.8%
 
ValueCountFrequency (%) 
-1.9769756031< 0.1%
 
-1.9649978991< 0.1%
 
-1.9491088681< 0.1%
 
-1.9489549641< 0.1%
 
-1.9460391191< 0.1%
 
-1.9449690251< 0.1%
 
-1.9392383691< 0.1%
 
-1.9384228051< 0.1%
 
-1.9380524111< 0.1%
 
-1.9375527141< 0.1%
 
ValueCountFrequency (%) 
1191.0008374< 0.1%
 
1140.3532331< 0.1%
 
1126.7654311< 0.1%
 
1072.9579791< 0.1%
 
1072.7930691< 0.1%
 
1071.6042261< 0.1%
 
1027.5551661< 0.1%
 
1022.2011751< 0.1%
 
1017.4030281< 0.1%
 
1017.383181< 0.1%
 

class
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size140.0 KiB
0
16259
1
 
1639
ValueCountFrequency (%) 
01625990.8%
 
116399.2%
 

Interactions

2020-08-10T18:26:01.928479image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:02.305563image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:02.673479image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:03.020554image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:03.386486image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:03.746481image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:04.084483image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:04.412481image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:04.769494image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:05.163477image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:05.533479image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:05.896480image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:06.265560image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:06.765476image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-08-10T18:26:10.337486image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-08-10T18:26:14.700482image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:15.074486image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:15.451483image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:15.860478image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:16.221481image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:16.589481image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:16.973480image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:17.328559image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-08-10T18:26:26.940889image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-08-10T18:26:27.632809image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:27.994883image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-08-10T18:26:28.669809image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:28.982811image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:29.363889image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:29.690888image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:30.007814image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:30.371811image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Correlations

2020-08-10T18:26:37.524617image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-10T18:26:37.987536image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-10T18:26:38.430536image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-10T18:26:38.882540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-10T18:26:31.027860image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-08-10T18:26:31.825812image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Sample

First rows

df_indexmean_int_pfstd_pfex_kurt_pfskew_pfmean_dmstd_dmkurt_dmskew_dmclass
01140.56250055.683782-0.234571-0.6996483.19983319.1104267.97553274.2422250
12102.50781258.8824300.465318-0.5150881.67725814.86014610.576487127.3935800
23103.01562539.3416490.3233281.0511643.12123721.7446697.73582263.1719090
34136.75000057.178449-0.068415-0.6362383.64297720.9592806.89649953.5936610
4588.72656240.6722250.6008661.1234921.17893011.46872014.269573252.5673060
5693.57031246.6981140.5319050.4167211.63628814.54507410.621748131.3940040
67119.48437548.7650590.031460-0.1121680.9991649.27961219.206230479.7565670
78130.38281239.844056-0.1583230.3895401.22073614.37894113.539456198.2364570
89107.25000052.6270780.4526880.1703472.33194014.4868539.001004107.9725060
910107.25781239.4964880.4658821.1628774.07943124.9804187.39708057.7847380

Last rows

df_indexmean_int_pfstd_pfex_kurt_pfskew_pfmean_dmstd_dmkurt_dmskew_dmclass
178881788998.72656250.4078230.5651240.2452310.5702349.01128522.018589561.8337870
1788917890126.62500055.7218260.002946-0.3032180.5342818.58888223.913761660.1970350
1789017891143.67187545.302647-0.0457690.3536435.17391326.4623455.70665133.8026130
1789117892118.48437550.608483-0.029059-0.0274940.4222418.08668427.446113830.6385500
178921789396.00000044.1931130.3886740.2813441.87123715.8337469.634927104.8216230
1789317894136.42968859.847421-0.187846-0.7381231.29682312.16606215.450260285.9310220
1789417895122.55468849.4856050.1279780.32306116.40969944.6268932.9452448.2970920
1789517896119.33593859.9359390.159363-0.74302521.43060258.8720002.4995174.5951730
1789617897114.50781253.9024000.201161-0.0247891.94648813.38173110.007967134.2389100
178971789857.06250085.7973401.4063910.089520188.30602064.712562-1.5975271.4294750